Labor biomarkers, methods comprising same, and methods targeting same

ABSTRACT

The present invention provides methods of predicting or detecting labor in a female subject and methods of testing a compound for an ability to delay the onset of labor. The present invention also provides methods of testing a labor marker useful in the diagnostic methods, isolated peptides identified in the present invention, methods for inhibiting labor, utilizing the peptides, and kits comprising methods of the present invention.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority of U.S. Provisional Application Ser.No. 60/646,589, filed Jan. 26, 2005. This application is herebyincorporated in its entirety by reference herein.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

The invention described herein was supported in part by grants from theFogarty International Center (Grant No. D43TW000671) and the NationalInstitutes of Child Health and Human Development (Grant Nos. T32HD007305and R01-HD034612). The government has certain rights in the invention.

FIELD OF THE INVENTION

The present invention provides methods of predicting or detecting laborin a female subject and methods of testing a compound for an ability todelay the onset of labor. The present invention also provides methods oftesting a labor marker useful in the diagnostic methods, isolatedpeptides identified in the present invention, methods for inhibitinglabor, utilizing the peptides, and kits used to perform methods of thepresent invention

BACKGROUND OF THE INVENTION

Effective management strategies for identifying and treating pretermlabor are required to prevent preterm birth. Early births resulting frompreterm labor result in a heavy burden of infant mortality andmorbidity. Preterm birth is a factor in three-quarters of neonatalmortality and one-half of long-term neurologic impairment in children.

Early detection and management of preterm labor helps to prevent pretermbirth and its potential neonatal sequelae, which include respiratorydistress syndrome, sepsis, intraventricular hemorrhage, necrotizingenterocolitis, patent ductus arteriosus, and hyperbilirubinemia;however, widespread treatment of women with signs and symptoms ofpreterm labor has not significantly reduced the prevalence of pretermbirth in the United States, underscoring the need to improve currentmethods for detecting preterm labor.

SUMMARY OF THE INVENTION

The present invention provides methods of predicting or detecting labor,either full-term labor or preterm labor, comprising the assaying of abiological fluid for the presence of marker proteins or peptides.Measuring one or more marker proteins or peptides, and comparing theiramounts to reference standards, predicts the pregnancy status of thesubject.

In one embodiment, depicted in FIG. 4B, right branch, the presentinvention provides a method of predicting or detecting labor in a femalesubject, comprising (a) determining an amount of a first peptide in abiological sample of the female subject, the first peptide having anamino acid sequence set forth in SEQ ID No: 10; (b) comparing the amountof a first peptide to a reference standard for the first peptide; (c)determining an amount of a second peptide, the second peptide having anamino acid sequence set forth in SEQ ID No: 7, wherein the amount is anamount in the biological sample wherein the first peptide was detectedor an additional biological sample of the female subject; and (d)comparing the amount of a second peptide to a reference standard for thesecond peptide.

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a first peptide is higher than an upper limit of arange defined by the reference standard for the first peptide; and (i b)the amount of a second peptide is higher than an upper limit of a rangedefined by the reference standard for the second peptide.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a first peptide is higher thanan upper limit of a range defined by the reference standard for thefirst peptide; and (ii b) the amount of a second peptide is lower than alower limit of a range defined by the reference standard for the secondpeptide.

In another embodiment, the present invention provides a method ofpredicting or detecting labor in a female subject, comprising (a)determining an amount of a first peptide in a biological sample of thefemale subject, the first peptide having an amino acid sequence setforth in SEQ ID No: 10; (b) comparing the amount of a first peptide to areference standard for the first peptide; (c) determining an amount of ahemoglobin-derived peptide, wherein the amount is an amount in thebiological sample wherein the first peptide was detected or anadditional biological sample of the female subject; and (d) comparingthe amount of a second peptide or protein to a reference standard forthe second peptide or protein. In another embodiment, thehemoglobin-derived peptide has an amino acid sequence selected from thesequences set forth in SEQ ID No: 8, 9, 11, and 12. Each possibilityrepresents a separate embodiment of the present invention.

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a first peptide is higher than an upper limit of arange defined by the reference standard for the first peptide; and (i b)the amount of a hemoglobin-derived peptide is within a labor rangedefined by the reference standard for the hemoglobin-derived peptide.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a first peptide is higher thanan upper limit of a range defined by the reference standard for thefirst peptide; and (ii b) the amount of a hemoglobin-derived peptide iswithin a non-labor range defined by the reference standard for thehemoglobin-derived peptide.

In another embodiment, the present invention provides a method oftesting a compound for an ability to delay labor onset, comprising (a)determining a clinical state of a first pregnant subject by the methodof the present invention, wherein the first pregnant subject has beencontacted with the compound; (b) determining a clinical state of asecond pregnant subject by the method of the present invention, whereinthe second female subject has not been contacted with the compound; and(c) comparing the clinical state of a first pregnant subject to theclinical state of a second pregnant subject, whereby a decreasedincidence of the labor onset in the first pregnant subject relative tothe second pregnant subject indicates that the compound has an abilityto delay an onset of a labor.

In another embodiment, the present invention provides an isolatedpeptide having an amino acid sequence selected from the sequences setforth in SEQ ID No: 1-6. Each peptide represents a separate embodimentof the present invention.

In another embodiment, the present invention provides an isolatedpeptide having an amino acid sequence selected from the sequences setforth in SEQ ID No: 7-12. Each peptide represents a separate embodimentof the present invention.

In another embodiment, the present invention provides a method forinhibiting induction of labor in a subject, comprising contacting thesubject with a compound or antibody that prevents an interaction betweena peptide having an amino acid sequence set forth in SEQ ID No: 9 and areceptor of the peptide.

In another embodiment, the present invention provides a method forarresting labor in a subject, comprising contacting the subject with acompound or antibody that prevents an interaction between a peptidehaving an amino acid sequence set forth in SEQ ID No: 9 and a receptorof the peptide.

In another embodiment, the present invention provides a method forinhibiting induction of labor in a subject, comprising contacting thesubject with a compound or antibody that interacts with a peptide havingan amino acid sequence set forth in SEQ ID No: 9.

In another embodiment, the present invention provides a method forarresting labor in a subject, comprising contacting the subject with acompound or antibody that interacts with a peptide having an amino acidsequence set forth in SEQ ID No: 9.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Surface-enhanced laser desorption/ionization, time-of-flight,mass spectrometry (SELDI-TOF-MS) Biological ProteinChip ArrayMethodology. A) Each spot had a specific surface chemistry and wasexposed to a buffered solution prior to sample spotting. B) Sample wasdiluted in a buffered solution (pH 4) and spotted onto the chip. C)Extraneous proteins were removed via washing with the pH 4 buffer. D)The chip was dried and energy absorbing molecules (EAM, 20% CHCA) wereadded to each spot. E) and F) The bound proteins were volatilized with alaser, and direct mass assessments were made using mass spectrometry.

FIG. 2. Multivariate Analysis of Amnion Peaks. Spectra from each samplewere collected, normalized by the total ion current, and analyzed usingBiomarker Wizard software. A) Molecular weight (as determined bymass/charge (M/Z) ratio) and respective p-values of the 17 peaks foundto be statistically significantly different between amnion collectedafter c-section compared with amnion collected after vaginal delivery.B) An example of a decision tree established by the CART softwareprogram. CART was used to analyze the 17 peaks and establish decisiontrees (also referred to as classification trees) based on peak data.This 5-noded tree correctly classified 96% CS and 90% of labored amnionsamples. Peaks utilized in the decision tree are indicated by hexagons.Sorting mechanism based on the intensity of specific peaks is indicatedon each diagonal line. Terminal nodes are indicated by the squares.

FIG. 3. Amnion Peak Identities. Several statistically significant peakswere chosen to be identified using PCI-QTOF. Each portion of the figurecorresponds to a specific peak and contains a bar graph indicating theaverage intensity levels (and standard errors) in the labor andc-section samples, a typical spectrum, and the identity of the peak. The2.529 kDa peak (A) was identified as a fragment of serum albumin. The2.928 kDa peak (B), the 3.346 kDa (C), and the 3.199, 3.214, 3.231 kDapeaks (D) were identified as fragments of the α-chain of hemoglobin withand without oxidized amino acids.

FIG. 4. Analysis of Cervicovaginal Secretions. Spectra from each samplewere collected, normalized by the total ion current, and analyzed usingBiomarker Wizard software. A) Molecular weight and respective p-valuesof the 25 peaks found to be statistically different betweencervicovaginal secretions collected at term from patients experiencinglabor and patients who are not in labor. B) An example of a decisiontree established by the CART software program. CART was used to analyzethe 25 peaks and establish decision trees based on peak data. This4-noded tree correctly classified 95% no labor and 100% of laboredcervicovaginal secretion samples. Peaks utilized in the decision treeare indicated by hexagons. Sorting mechanism based on the intensity ofspecific peaks is indicated on each diagonal line. Terminal nodes areindicated by the colored squares

FIG. 5. Cervicovaginal Peak Identities. Several statisticallysignificant peaks were chosen to be identified using PCI-QTOF. Eachportion of the figure corresponds to a specific peak and contains a bargraph indicating the average intensity levels (and standard errors) inthe labor and no labor samples, a typical spectrum, and the identity ofthe peak. The 1.869 kDa peak (A) and 1 peptide contained in the 3.277kDa peak (E) were identified as fragments of β-chain hemoglobin, and the3.196 kDa peak (C) and the 3.228 kDa peak (D) have identical amino acidssequences, but the increased MW of the 3.228 kDa peak is due to oxidizedtryptophan and histidine residues. 2.022 kDa peak (B), the 3.196 kDapeak (C), the 3.228 kDa peak (D), were all identified as fragments ofα-chain hemoglobin.

FIG. 6. Amnion and vaginal samples have complementary peak profiles. Anumber of the peaks exhibited decreased intensity in amniotic tissue asa result of labor and increased intensity in cervicovaginal secretionsas a result of labor. For example, peaks in the 3.2 kDa peak clusterwere found to be diagnostic for labor in both amniotic tissue andcervicovaginal secretions.

FIG. 7. (A) ROC curves of hemoglobin and the intensity values of the1.869 kDa and 3.198 kDa peaks. (B) ROC curves of hemoglobin incombination with the intensity values of each of the 1.869 kDa and 3.198kDa peaks. (C) ROC curves from logistic regression model for predictinglabor, comparing the logistic model which combines hemoglobin andintensity of the 3.198 kDa peak (“hemo+intens1”; open circles) vs.hemoglobin and intensity of the 1.869 kDa peak (“hemo+intens2”; closedcircles). (D) ROC curves comparing logistic model for hemoglobin alone(“hemo”; open circles) vs. a logistic regression model which combinedhemoglobin and intensity of the 1.869 kDa peak (“hemo+intens2”; closedcircles). (E) ROC curves from logistic regression model for labor,comparing the combination of hemoglobin and intensity of the 1.869 kDapeak (“hemo+intens2”; open circles) vs. intensity of the 1.869 kDa peakalone (“intens2”; closed circles).

FIG. 8. Raw data for combined term and preterm labor samples.

FIG. 9. Identities of cervicovaginal peaks. Several of the peaks thatwere significantly increased in cervicovaginal fluid from laboring womenwere identified using PCI-QTOF. Each portion of the figure correspondsto a specific peak and contains a histogram indicating the intensitydifferences between labor and no labor samples, a typical spectrum, andthe amino acid sequence of the peak. The 1.869 kDa peak (FIG. 9A-SEQ IDNO: 10) and 1 peptide contained in the 3.277 kDa peak (FIG. 9E-Toppeptide SEQ ID NO: 12; bottom peptide SEQ ID NO: 11) were identified asfragments of β-chain hemoglobin, and the 3.196 kDa peak (FIG. 9C-SEQ IDNO: 7) and the 3.228 kDa peak (FIG. 9D-SEQ ID NO: 8) have identicalamino acids sequences, but the increased MW of the 3.228 kDa peak is dueto oxidized tryptophan and histidine residues. 2.022 kDa peak (FIG.9B-SEQ ID NO: 9), the 3.196 kDa peak (FIG. 9C-SEQ ID NO: 7), the 3.228kDa peak (FIG. 9D-SEQ ID NO: 8), were all identified as fragments ofα-chain hemoglobin. The underlined residues in the 3.228 kDa fragmentare oxidized.

FIG. 10. The 2.022 kDa fragment potentiates the action of bradykinin,oxytocin and PGF2-α on rat aortic smooth muscle cells (A). Bradykinin(BK) administration elicited a dose-dependent decrease in cell area withan IC₅₀ of 5 nM. The potentiation peptide (PP) augmented the 5 nM BKresponse by dramatically decreasing cell area compared to 5 nM BK in thepresence of control peptide (CP), (P<0.0001). Oxytocin (OT)administration elicited a dose-dependent decrease in cell area with anIC₅₀ of 8 nM. The potentiation peptide (PP) augmented the 10 nM OTresponse by dramatically decreasing cell area compared to 10 nM OT inthe presence of control peptide (CP), (P<0.0011). PGF2-α administrationelicited a dose-dependent decrease in cell area with an IC₅₀ of 0.56 nM.The potentiation peptide (PP) augmented the 0.56 nM PG response bydramatically decreasing cell area compared to 0.56 nM PG in the presenceof control peptide (CP), (P<0.0001). Asterisks indicate statisticallysignificant differences (P<0.05) between the CP and PP in all treatmentgroups.

FIG. 11. The 2.022 kDa α-Hb fragment potentiates the action of oxytocinon rat uterus. Pregnant Wistar rat uteri were treated with 1 nm Oxytocin+/−100 μM of the 2.022 kDa peptide or a control peptide, 0.1 mldistilled water (vehicle) or 30 μM phosphoramidon (positive control).The 2.022 kDa peptide increased uterine tissue contractility in thepresence of oxytocin by approximately 30% compared to control peptide inthe presence of oxytocin.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides methods of predicting or detecting labor,either full-term labor or preterm labor, comprising the assaying of abiological fluid for the presence of marker proteins or peptides.Measuring one or more marker proteins or peptides, and comparing theiramounts to reference standards, predicts the labor status of thesubject.

As provided herein, the findings of Examples 2 and 4 show that variousproteins and peptides correlate with the labor status of a subject.

In one embodiment, depicted in FIG. 4B, right branch, the presentinvention provides a method of predicting or detecting labor in a femalesubject, comprising (a) determining an amount of a first peptide in abiological sample of the female subject, the first peptide having anamino acid sequence set forth in SEQ ID No: 10; (b) comparing the amountof a first peptide to a reference standard for the first peptide; (c)determining an amount of a second peptide, the second peptide having anamino acid sequence set forth in SEQ ID No: 7, wherein the amount is anamount in the biological sample wherein the first peptide was detectedor an additional biological sample of the female subject; and (d)comparing the amount of a second peptide to a reference standard for thesecond peptide.

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a first peptide is higher than an upper limit of arange defined by the reference standard for the first peptide; and (i b)the amount of a second peptide is higher than an upper limit of a rangedefined by the reference standard for the second peptide.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a first peptide is higher thanan upper limit of a range defined by the reference standard for thefirst peptide; and (ii b) the amount of a second peptide is lower than alower limit of a range defined by the reference standard for the secondpeptide.

In another embodiment, depicted in FIG. 4B, left branch, the presentinvention provides a method of predicting or detecting labor in a femalesubject, comprising (a) determining an amount of a first peptide in abiological sample of the female subject, the first peptide having anamino acid sequence set forth in SEQ ID No: 10; (b) comparing the amountof a first peptide to a reference standard for the first peptide; (c)determining an amount of a second protein or peptide, the second proteinor peptide having a molecular mass of about 3.908 kilodaltons (kDa),wherein the amount is an amount in the biological sample wherein thefirst peptide was detected or an additional biological sample of thefemale subject; and (d) comparing the amount of a second protein orpeptide to a reference standard for the second protein or peptide. Thediagnosis is made based on the outcome of assessing the levels of thefour proteins, as will now be described:

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a first peptide is lower than a lower limit of arange defined by the reference standard for the first peptide; and (i b)the amount of a second protein or peptide is lower than a lower limit ofa range defined by the reference standard for the second protein orpeptide.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a first peptide is lower than alower limit of a range defined by the reference standard for the firstpeptide; and (ii b) the amount of a second protein or peptide is higherthan an upper limit of a range defined by the reference standard for thesecond protein or peptide.

“Labor” in methods of the present invention refers, in one embodiment,to cervical dilation. In another embodiment, “labor” refers to cervicaleffacement. In another embodiment, “labor” refers to latent phase labor.In another embodiment, “labor” refers to active phase labor. In anotherembodiment, “labor” refers to uterine contractions. In anotherembodiment, “labor” refers to rupture of membranes. In anotherembodiment, “labor” refers to any other definition thereof in the art.Each definition of labor represents a separate embodiment of the presentinvention.

The peptide of SEQ ID No: 7 was found in several oxidation states inamnion and cervicovaginal fluids (Examples 2 and 4). In one embodimentof methods of the present invention, this peptide does not comprise anyoxidized amino acids. In another embodiment, this peptide does compriseone or more oxidized amino acids. Each oxidation state of the peptiderepresents a separate embodiment of the present invention.

Methods of defining a range using a reference standard are well known inthe art. In one embodiment of methods of the present invention, therange is defined using a statistical method. In one embodiment, thestatistical method is a CART analysis method. In another embodiment, thestatistical method is any other statistical method known in the art. Inanother embodiment, the range is defined by an empirical determinationof the best range to use for classifying the subjects; for example, bycomparing the predictive power of methods utilizing different ranges.Each method of determining the range of values represents a separateembodiment of the present invention.

In one embodiment, a range of values of a method of the presentinvention has both an upper and a lower limit For example, a range canbe between 5 and 100,000, 10 and 50,000, 20 and 10,000, 100 and 5000, 1and 1000, 5 and 1000, 10 and 500, 50 and 200, 80 and 100, 0.1 and 5,0.01 and 1, 0.005 and 0.4, or any other set of two numbers. In anotherembodiment, the range has only an upper limit; for example, eitherbelow, or below or equal to 100,000, 30,000, 10,000, 3000, 1000, 500,100, 30, 10, 5, 1, 0.5, 0.2, 0.02, 0.005, 0.001, or any other number. Inanother embodiment, the range has only a lower limit; for example,either above, or above or equal to 100,000, 30,000, 10,000, 3000, 1000,500, 100, 30, 10, 5, 1, 0.5, 0.2, 0.02, 0.005, 0.001, or any othernumber. In one embodiment, the range is quantitative (e.g. a range ofvalues). In another embodiment, the range is qualitative. Determiningwhether an amount falls within a qualitative range is assessed, in oneembodiment, by a qualitative method, e.g, a calorimetric assay, theformation of a precipitate, etc, in a method of the present invention.In another embodiment, a range is absolute; e.g, the same for allsubjects. In another embodiment, the range is relative. The relativerange is determined, in one embodiment, by comparison to an amount of adifferent protein or peptide in the biological sample. In anotherembodiment, the relative range is determined by comparison to aninternal standard in the biological sample. In another embodiment, therelative range is determined by comparison to an amount of a protein orpeptide in a different biological sample from the subject. Each type ofrange represents a separate embodiment of the present invention.

An “amount” of a marker in a method of the present invention refers, inone embodiment, to an absolute amount in the biological sample. Inanother embodiment, “amount” refers to a concentration in the sample. Inanother embodiment, “amount” refers to an amount that is free, e.g, notbound to a component of the sample—for example, the hematocrit, aparticular population of cells, or a particular population of proteins,or lipids or other biological molecules. In another embodiment, “amount”refers to an amount that is bound to the component. Each possibilityrepresents a separate embodiment of the present invention.

The peptide detected in methods of the present invention is, in oneembodiment, a protein. In another embodiment, the peptide is a fragmentof a protein. In another embodiment, the peptide is a proteolyticproduct of a protein. In another embodiment, the peptide is a hormone.In another embodiment, the peptide is any other type of peptide known inthe art. Each type of peptide represents a separate embodiment of thepresent invention.

In another embodiment, the present invention provides a method ofpredicting or detecting labor in a female subject, comprising (a)determining an amount of a first peptide in a biological sample of thefemale subject, the first peptide having an amino acid sequence setforth in SEQ ID No: 10; (b) comparing the amount of a first peptide to areference standard for the first peptide; (c) determining an amount of ahemoglobin-derived peptide, the hemoglobin-derived peptide, wherein theamount is an amount in the biological sample wherein the first peptidewas detected or an additional biological sample of the female subject;and (d) comparing the amount of a second peptide or protein to areference standard for the second peptide or protein. The findings ofExample 3 demonstrate that each of the peptides or proteins of SEQ IDNo: 7-12 and each of the other peptides in Tables 1 and 2 are useful inpredicting or detecting labor, both individually and in combination. Inanother embodiment, the hemoglobin-derived peptide has an amino acidsequence selected from the sequences set forth in SEQ ID No: 8, 9, 11,and 12. Each possibility represents a separate embodiment of the presentinvention.

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a first peptide is higher than an upper limit of arange defined by the reference standard for the first peptide; and (i b)the amount of a hemoglobin-derived peptide is within a labor rangedefined by the reference standard for the hemoglobin-derived peptide.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a first peptide is higher thanan upper limit of a range defined by the reference standard for thefirst peptide; and (ii b) the amount of a hemoglobin-derived peptide iswithin a non-labor range defined by the reference standard for thehemoglobin-derived peptide.

As provided herein, the findings of Example 6 show the results of aChemstrip® urine hemoglobin test can be combined with the amount of apeptide of the present invention to determine the labor status of asubject. In another embodiment, the present invention provides a methodof predicting or detecting labor in a female subject, comprising (a)determining an amount of a peptide or protein, wherein the amount is anamount in a biological sample of the female subject; (b) comparing theamount of a peptide or protein to a reference standard for the peptideor protein; (c) administering a hemoglobin test to the female subject;and (d) comparing a result of the hemoglobin test to a referencestandard for the hemoglobin test.

Attainment of outcome (i) indicates, in this embodiment, that the femalesubject is in labor. Outcome (i) is defined, in this embodiment, as both(i a) the amount of a peptide or protein is within a labor range definedby the reference standard for the peptide or protein; and (i b) theresult of a hemoglobin test is within a labor range defined by thereference standard for the hemoglobin test.

Attainment of outcome (ii) indicates, in this embodiment, that thefemale subject is not in labor. Outcome (ii) is defined, in thisembodiment, as both (ii a) the amount of a peptide or protein is higherthan an upper limit of a range defined by the reference standard for thepeptide or protein; and (ii b) the result of a hemoglobin test is withina non-labor range defined by the reference standard for the hemoglobintest.

In another embodiment, the labor ranges and non-labor ranges of thehemoglobin test in a method of the present invention are the same rangesas those used in the other applications of the hemoglobin test. Inanother embodiment, the labor ranges and non-labor ranges are the sameranges as those used in the other applications of the hemoglobin test.Each possibility represents a separate embodiment of the presentinvention.

The terms “labor range” and “non-labor range” refer, in one embodiment,to ranges of values or amounts that are observed in subjects in laborand not in labor, respectively. For example, for the 3.908 kDa peptide,the labor-range is, in one embodiment, a peak height of less than orequal to 0.724, and the non-labor range is a peak height of greater than0.724. In another embodiment, the labor-range for the 3.196 kDa peptideis, in one embodiment, a peak height of greater than 0.357, and thenon-labor range is a peak height of less than or equal to 0.357. Oneskilled in the art will understand that the labor and non-labor rangescan be defined by a wide range of numbers, and will vary according tothe assay used, the exact protocol followed, the patient population, andother variables. Each labor range and non-labor range represents aseparate embodiment of the present invention.

In one embodiment, the hemoglobin test is a urine hemoglobin test. Inanother embodiment, the hemoglobin test is a hemoglobin test of anyother biological fluid or tissue known in the art. Each hemoglobin testrepresents a separate embodiment of the present invention.

In one embodiment, a peptide or protein detected in a method of presentinvention has an amino acid sequence selected from the sequences setforth in SEQ ID No: 7 or 10. In another embodiment, the peptide orprotein has an amino acid sequence selected from the sequences set forthin SEQ ID No: 8, 9, 11, and 12. In another embodiment, the peptide orprotein is any other peptide or protein identified by a method of thepresent invention. Each peptide or protein represents a separateembodiment of the present invention.

In another embodiment, the present invention provides a method ofpredicting or detecting labor in a female subject, comprising (a)determining an amount of one or more peptides or proteins in abiological sample of the female subject, the peptides or proteins havingan amino acid sequence selected from the sequences set forth in SEQ IDNo: 1-6 and 12; and (b) comparing the amounts of the peptides orproteins to respective reference standards for the peptides or proteins.A decision tree is used, in another embodiment, to classify the samples,similar to the above methods. In another embodiment, one or more of theother peptides or proteins in Table 2 is used instead of the peptideshaving the sequences set forth in SEQ ID No: 1-6 and 12.

In one embodiment, the peptide or protein detected in a method ofpresent invention has an amino acid sequence set forth in SEQ ID No: 5.In another embodiment, the peptide or protein has an amino acid sequenceset forth in SEQ ID No: 6. In other embodiments, the peptide or proteinhas an amino acid sequence selected from the sequences set forth in SEQID No: 1-4 and 7-12. In another embodiment, the peptide or protein isone of the peptides or proteins set forth in Table 2. Each possibilityrepresents a separate embodiment of the present invention.

In another embodiment, methods of the present invention comprise the useof one or more additional markers identified by methods of the presentinvention (e.g. Example 9), in combination with and/or instead of theproteins and peptides identified in the present invention. In anotherembodiment, methods of the present invention comprise combining amountsof peptides of the present invention with maternal age, gestational age,reproductive history, serum hCG level, and/or other known factors, toimprove their accuracy in predicting and/or detecting the onset of labor(Examples 10-11). Each method represents a separate embodiment of thepresent invention.

In another embodiment, the present invention provides a method oftesting a compound for an ability to delay labor onset, comprising (a)determining a clinical state of a first pregnant subject by the methodof the present invention, wherein the first pregnant subject has beencontacted with the compound; (b) determining a clinical state of asecond pregnant subject by the method of the present invention, whereinthe second female subject has not been contacted with the compound; and(c) comparing the clinical state of a first pregnant subject to theclinical state of a second pregnant subject, whereby a decreasedincidence of the labor onset in the first pregnant subject relative tothe second pregnant subject indicates that the compound has an abilityto delay an onset of a labor. In another embodiment, the clinical statethat is determined is selected from “in labor” or “not in labor.” Eachpossibility represents a separate embodiment of the present invention.

In one embodiment, multiple female subjects are tested by the abovemethod. The use of multiple female subjects increases, in anotherembodiment, the statistical significance of the results obtained.

Each method of the present invention for determining a clinical state ofa pregnant subject can be used in steps (a) and (b) of the above methodof testing a compound for an ability to delay labor onset, and the useof each such method represents a separate embodiment of the presentinvention.

In another embodiment, the present invention provides a method oftesting a marker for an ability to predict or detect labor, comprising(a) determining an amount of the marker in a biological sample from apregnant subject; (b) determining a labor status of the pregnantsubject; (c) repeating steps (a)-(b) for a population of additionalpregnant subjects; and (d) ascertaining whether a correlation existsbetween the amount and the labor status, wherein a presence of thecorrelation indicates that the marker is useful in predicting ordetecting labor. In another embodiment, the labor status is selectedfrom: in labor and not in labor. Each possibility represents a separateembodiment of the present invention.

In another embodiment, the present invention provides a method oftesting a marker for an ability to predict or detect labor, comprising(a) determining an amount of the marker in a biological sample from apregnant subject; (b) determining a clinical factor of the femalesubject; (c) determining a labor status of the pregnant subject; (d)repeating steps (a)-(c) for a population of additional pregnantsubjects; and (e) ascertaining whether a correlation exists between (i).a mathematical function of the amount and the clinical factor; and (ii).the pregnancy status, wherein a presence of the correlation indicatesthat the marker is useful in predicting or detecting labor. In anotherembodiment, the labor status is selected from: in labor and not in laborEach possibility represents a separate embodiment of the presentinvention.

In one embodiment, the marker is a protein. In another embodiment, themarker is a peptide. In another embodiment, the marker is a proteolyticproduct of a protein or peptide of the present invention. In anotherembodiment, the marker is a variant of a protein or peptide of thepresent invention. In another embodiment, the marker is a homologue of aprotein or peptide of the present invention. Each possibility representsa separate embodiment of the present invention.

In one embodiment, the clinical factor is maternal age. In anotherembodiment, the clinical factor is gestational age. In anotherembodiment, the clinical factor is a reproductive history. In anotherembodiment, the clinical factor is any other clinical factor known inthe art. Each clinical factor represents a separate embodiment of thepresent invention.

“Labor,” in one embodiment, refers to term labor. In another embodiment,“labor” refers to preterm labor. The findings of Example 7 demonstratethat the methods of the present invention can be used to detect orpredict both term and preterm labor. In another embodiment, “labor”refers to induced labor. In another embodiment, “labor” refers tospontaneous labor. Each type of labor represents a separate embodimentof the present invention.

In one embodiment, the step of determining the amount of one or moreproteins or peptides in a method of the present invention comprises animmunological assay. In one embodiment, the immunological assay is aradio-immunoassay (RIA). In another embodiment, the immunological assayis an enzyme-linked immunosorbent assay (ELISA). In another embodiment,the immunological assay is a sandwich immunoassay. In anotherembodiment, the immunological assay is any other immunological assayknown in the art. In one embodiment, the immunological assay is used inplace of the mass spectrometry assays described in the Examples, oncesequence information is determined for the marker peptides identified.Each immunological assay represents a separate embodiment of the presentinvention.

Methods of performing immunological assays are well known in the art,and are described, for example, in Current Protocols in Immunology, JohnWiley & Sons, 2004. Each immunological assay represents a separateembodiment of the present invention.

In another embodiment, the step of determining the amount of one or moreproteins or peptides in a method of the present invention comprises asurface-enhanced laser desorption/ionization (SELDI) assay. In oneembodiment, the SELDI utilizes a weak cation exchange (WCX2) chemistry.In another embodiment, the SELDI utilizes an Immobilized Metal AffinityCapture (IMAC) chemistry. In one embodiment, the IMAC chemistrycomprises a copper ion. In another embodiment, the chemistry is similarto WCX2 chemistry (e.g. an improved or altered version thereof). Inanother embodiment, the chemistry is similar to IMAC chemistry. Eachpossibility represents a separate embodiment of the present invention.

In another embodiment, the step of determining the amount of one or moreproteins or peptides in a method of the present invention comprises amass spectrometry assay. In another embodiment, the step comprises anyother method for determining an amount of a peptide that is known in theart. Each possibility represents a separate embodiment of the presentinvention.

In one embodiment, the biological sample or the additional biologicalsample utilized in a method of the present invention is a cervicovaginalsecretion. In another embodiment, the biological sample or theadditional biological sample is a urine sample. In another embodiment,the biological sample or the additional biological sample is a serumsample. In another embodiment, the biological sample or the additionalbiological sample is a blood plasma sample. In another embodiment, thebiological sample or the additional biological sample is a salivasample. In another embodiment, the biological sample or the additionalbiological sample is a tissue. In another embodiment, the biologicalsample or the additional biological sample is a fluid. In anotherembodiment, the biological sample and the additional biological sampleare derived from the same tissue or fluid. In another embodiment, thebiological sample and the additional biological sample are derived fromdifferent tissues or fluids. In one embodiment, biological samples arederived from three or more different tissues or fluids are utilized.Each possibility represents a separate embodiment of the presentinvention.

In another embodiment, the step of ascertaining whether a correlationexists in a method of the present invention utilizes a classificationand regression tree (CART) analysis. CART analysis was used in Examplesof the present invention to identify protein peaks that correlate withlabor, and can be similarly used for any other indicator of the statusof a subject. Use of CART analysis is well known in the art, and isdescribed, for example, in Vlahou A et al, J Biomed Biotechnol. 2003;2003(5):308-314.

In another embodiment, the step of ascertaining is performed by anyother statistical method known in the art; for example, a Pearsoncorrelation, a canonical correlations analysis, a correspondenceanalysis, a path analysis, a cluster analysis, an equivalence test, alogistic regression model, a model selection technique, etc. Eachstatistical method represents a separate embodiment of the presentinvention.

Using these methods, each of the peaks identified in the presentinvention can be sequenced to determine the amino acid sequence of thepeptide or protein comprising them. In one embodiment, theidentification comprises amino acid sequencing, as described in Example8. In another embodiment, the identification comprises massdetermination, as described in Example 2 or Example 4. Immunological orother assays are then developed for detection of each of these proteins,further improving the assays of the present invention.

Methods of protein sequencing are well known in the art, and aredescribed, for example, in Lodish et al, Molecular Cell Biology, FourthEdition, W. H. FREEMAN, 2000; and Berg et al, Biochemistry, FifthEdition, 2002). Each protein sequencing method represents a separateembodiment of the present invention.

In another embodiment, the present invention provides an isolatedpeptide having an amino acid sequence selected from the sequences setforth in SEQ ID No: 1-6. Each peptide represents a separate embodimentof the present invention.

In another embodiment, the present invention provides an isolatedpeptide having an amino acid sequence selected from the sequences setforth in SEQ ID No: 7-12. Each peptide represents a separate embodimentof the present invention.

In another embodiment, the present invention provides an isolatedpeptide, selected from the peptides set forth in Table 2 herein.

In another embodiment, the present invention provides a homologue of anisolated peptide having an amino acid set forth in one of the sequencesof the present invention. In another embodiment, the present inventionprovides a variant of an isolated peptide having an amino acid set forthin one of the sequences of the present invention. Each possibilityrepresents a separate embodiment of the present invention.

The terms “homology,” “homologous,” etc, when in reference to anyprotein or peptide, refer in one embodiment, to a percentage of aminoacid residues in the candidate sequence that are identical with theresidues of a corresponding native polypeptide, after aligning thesequences and introducing gaps, if necessary, to achieve the maximumpercent homology, and not considering any conservative substitutions aspart of the sequence identity. Methods and computer programs for thealignment are well known in the art.

In another embodiment, the term “homology,” when in reference to anynucleic acid sequence similarly indicates a percentage of nucleotides ina candidate sequence that are identical with the nucleotides of acorresponding native nucleic acid sequence.

In another embodiment, “homology” refers to identity to one of SEQ IDNo: 1-12 of greater than 70%. In another embodiment, the identity isgreater than 75%. In another embodiment, the identity is greater than80%. In another embodiment, the identity is greater than 82%. In anotherembodiment, the identity is greater than 85%. In another embodiment, theidentity is greater than 86%. In another embodiment, the identity isgreater than 87%. In another embodiment, the identity is greater than88%. In another embodiment, the identity is greater than 89%. In anotherembodiment, the identity is greater than 90%. In another embodiment, theidentity is greater than 91%. In another embodiment, the identity isgreater than 92%. In another embodiment, the identity is greater than93%. In another embodiment, the identity is greater than 94%. In anotherembodiment, the identity is greater than 95%. In another embodiment, theidentity is greater than 96%. In another embodiment, the identity isgreater than 97%. In another embodiment, the identity is greater than98%. In another embodiment, the identity is greater than 99%. In anotherembodiment, the identity is 100%.

Homology is, in another embodiment, determined by computer algorithm forsequence alignment, by methods well described in the art. In anotherembodiment, computer algorithm analysis of nucleic acid sequencehomology includes the utilization of any number of software packagesavailable, such as, for example, the BLAST, DOMAIN, BEAUTY (BLASTEnhanced Alignment Utility), GENPEPT and TREMBL packages.

In another embodiment, homology is determined is via determination ofcandidate sequence hybridization, methods of which are well described inthe art (See, for example, “Nucleic Acid Hybridization” Hames, B. D.,and Higgins S. J., Eds. (1985); Sambrook et al., 1989, MolecularCloning, A Laboratory Manual, (Volumes 1-3) Cold Spring Harbor Press,N.Y.; and Ausubel et al., 1989, Current Protocols in Molecular Biology,Green Publishing Associates and Wiley Interscience, N.Y). in anotherembodiment, methods of hybridization are carried out under moderate tostringent conditions, to the complement of a DNA encoding a nativecaspase peptide. Hybridization conditions being, for example, overnightincubation at 42° C. in a solution comprising: 10-20% formamide, 5×SSC(150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6),5× Denhardt's solution, 10% dextran sulfate, and 20 μg/ml denatured,sheared salmon sperm DNA.

Protein and/or peptide homology for any amino acid sequence listedherein is determined, in one embodiment, by methods well described inthe art, including immunoblot analysis, or via computer algorithmanalysis of amino acid sequences, utilizing any of a number of softwarepackages available, via established methods. In other embodiments, theFASTA, BLAST, MPsrch or Scanps packages; Smith and Waterman algorithms,and/or global/local or BLOCKS alignments are used. Each method ofdetermining homology represents a separate embodiment of the presentinvention.

In another embodiment, the present invention provides a proteolyticproduct of a peptide of the present invention. The findings of Examples1-4 show that some of the same peptides are found in the amnion and incervicovaginal secretions. These findings and the findings of Example 5show that some biomarkers of labor, for the example the 3.2 kDa clusterof α-hemoglobin peptides and other peptides listed above, are stored inthe amnion and released with the onset of labor into other biologicalfluids and tissues, including, for example, cervicovaginal secretions,urine, serum, blood plasma, and saliva. After release from the amnion,the peptides are likely to be undergo additional proteolytic cleavage,thus generating shorter peptides.

In addition, the findings of Example 5 show that peptides depleted inthe amnion in subjects in labor are likely to be enriched in otherbiological fluids and tissues. Thus, in another embodiment, the presentinvention provides a method of predicting or detecting labor, comprisingmeasuring an amount of one or more of these peptides in one or morebiological fluids or tissues. Each peptide represents a separateembodiment of the present invention.

In another embodiment, a peptide detected by a method of the presentinvention is an indicator of uterine bleeding. In another embodiment,the uterine bleeding is due to decidual hemorrhage. In anotherembodiment, the uterine bleeding and/or decidual hemorrhage occurs inthe course of normal labor. In another embodiment, the uterine bleedingand/or decidual hemorrhage occurs as a pathological event. In anotherembodiment, the uterine bleeding and/or decidual hemorrhage triggerspreterm labor. Each possibility represents a separate embodiment of thepresent invention.

In another embodiment, the peptide is released or generated as a resultof activity of a matrix metalloproteinase (MMP) within the femalereproductive tract. In another embodiment, the activity of the MMP helpsdegrade extracellular matrix proteins in preparation for fetal membranerupture. In another embodiment, the activity of the MMP helps causecervical remodeling prior to delivery. In another embodiment, the MMP isa matrixin protein. In another embodiment, the MMP is a collagenaseprotein. In another embodiment, the presence of the 2.022 kDa peptide inthe cervicovaginal secretions during active labor is a consequence ofMMP degradation of Hb. Each possibility represents a separate embodimentof the present invention.

In another embodiment, the present invention provides a method forinhibiting induction of labor in a subject, comprising contacting thesubject with a compound or antibody that prevents an interaction betweena peptide having an amino acid sequence set forth in SEQ ID No: 9 and areceptor of the peptide. The findings of Example 12 show that thispeptide exhibits uterotonic potentiating activity, demonstrating thatthis peptide plays a role in labor induction. Thus, an antagonist ofthis peptide is useful in preventing labor.

The bradykinin receptor, oxytocin receptor, and prostaglandin receptorare all seven trans-membrane receptors with similar structure. Thus, thefindings of Example 12 show that a peptide having an amino acid sequenceset forth in SEQ ID No: 9 interacts, under the conditions utilized, witha seven trans-membrane receptor, and that the structure of the receptorfor the peptide is likely to resemble one of these receptors. Thus, inone embodiment, the receptor is a seven trans-membrane receptor. Inanother embodiment, the receptor is a bradykinin receptor. In anotherembodiment, the receptor is an oxytocin receptor. In another embodiment,the receptor is a prostaglandin receptor. Each possibility represents aseparate embodiment of the present invention.

In another embodiment, a peptide of the present invention binds aG-protein coupled receptors (GPCR), which these uterotonic agents bind.In another embodiment, the peptide interacts with a transmembrane domainof a GPCR domains. In another embodiment, the peptide alters GPCR ligandsensitivity.

In another embodiment, the peptide primes cells to becomehyper-responsive (in one embodiment, nonspecifically hyper-responsive)to a GCPR agonist. In another embodiment, this priming enhances signaltransduction to a heterotrimeric G-protein associated with the GPCR. Inanother embodiment, the signal transduction augments the release ofinositol triphosphate (IP₃) from the plasma membrane. In anotherembodiment, release of IP₃ enhances intracellular calcium release. Inanother embodiment, increased intracellular calcium transients activatecalmodulin, which, in turn, activates myosin light chain kinase (MLCK),ultimately increasing smooth muscle contraction (in one embodiment,uterine wall muscle contraction). In another embodiment, the GPCR is anα GPCR. In another embodiment, the GPCR is a β GPCR. In anotherembodiment, the GPCR is γ GPCR. Each possibility represents a separateembodiment of the present invention.

In another embodiment, a peptide of the present invention activatescalcium transients via the cyclic ADP-ribose (cADPR)-signaling pathway.In another embodiment, the peptide activates calcium transients bycausing influx of extracellular calcium. In another embodiment, thepeptide activates calcium transients by causing mobilization ofintracellular calcium. In another embodiment, the calcium transients areutertonin-generated calcium transients. In another embodiment, thepeptide potentiates the signaling by bradykinin receptors on decidualcells, those promoting responses that facilitate labor, Each possibilityrepresents a separate embodiment of the present invention,

Methods of performing uterine contraction assays are well known in theart, and are described, for example, in (Vane K R et al. Br J Pharmacol.48:629, 1973) and (Okawa T et al, Am J Obstet Gynecol 184(2): 84-9,2001). Each method represents a separate embodiment of the presentinvention.

In another embodiment, the present invention provides a method forarresting labor in a subject, comprising contacting the subject with acompound or antibody that prevents an interaction between a peptidehaving an amino acid sequence set forth in SEQ ID No: 9 and a receptorof the peptide.

In another embodiment, the present invention provides a method forinhibiting induction of labor in a subject, comprising contacting thesubject with a compound or antibody that interacts with a peptide havingthe amino acid sequence set forth in SEQ ID No: 9. In anotherembodiment, the compound or antibody inhibits a biological activity ofthe peptide.

In another embodiment, the present invention provides a method forarresting labor in a subject, comprising contacting the subject with acompound or antibody that interacts with a peptide having the amino acidsequence set forth in SEQ ID No: 9.

In another embodiment, the compound is a small-molecule inhibitor. Inanother embodiment, the compound is a macromolecule inhibitor. Inanother embodiment, the compound is itself a peptide. In anotherembodiment, the compound is any other type of compound or molecule knownin the art, for example a peptide, a peptidomimetic, a bivalentpolypeptide, a synthetic receptor (Park H et al, Proc Natl Acad Sci USA99(8): 5105-5109, 2002), etc. In another embodiment, the compound is acompetitive inhibitor of the interaction between the peptide and itsreceptor. In another embodiment, the compound is a non-competitiveinhibitor of the interaction. In another embodiment, the compound is aun-competitive inhibitor of the interaction. In another embodiment, thecompound inhibits the interaction by any other mechanism known in theart. Each type of inhibitor represents a separate embodiment of thepresent invention.

Methods of identifying small-molecule inhibitors of peptides, and oftheir interaction with biological molecules such as proteins, are wellknown in the art, and are described, for example, in Tanuma S et al(Biol Pharm Bull 27(7): 968-73, 2004; Raimundo B et al (J Med Chem47(12): 3111-30, 2004; Wang J et al, Proc Natl Acad Sci USA 97(13):7124-9; 2000; and Huang J et al, (Proc. Natl. Acad. Sci. USA 94:13396-13401, 1997). Each method represents a separate embodiment of thepresent invention.

In another embodiment, the inhibitor is tested in a cell-freedrug-screening assay. In one embodiment, a cell free drug screeningassay is performed by immobilizing either the peptide or its targetmolecule to a solid matrix (e.g. a bead) facilitate separation ofcomplexes of the peptide and its target molecule from their un-complexedforms, as well as to accommodate automation of the assay. Matrices arethen combined, in one embodiment, with the cell lysates (e.g., 35S-labeled) and the candidate compound, and the mixture incubated underconditions conducive to complex formation (e.g., at physiologicalconditions for salt and pH). Following incubation, the matrix is washedto remove any unbound label, and immobilized and radiolabel determinedeither directly, or in the supernatant after the complexes aredissociated, Alternatively, the complexes can be dissociated from thematrix and separated by SDS-PAGE, and the level of target molecule boundto the peptide found in the bead fraction can be quantitated from thegel using standard electrophoretic techniques. For example, either thepeptide or its target molecule can be immobilized utilizing conjugationof biotin and streptavidin using techniques well known in the art.Alternatively, antibodies reactive with the peptide but which do notinterfere with binding of the material to its target molecule can bederivatized to the wells of the plate, and the peptide trapped in thewells by antibody conjugation. Methods for detecting such complexesinclude immuno-detection of complexes using antibodies reactive with thetarget molecule, or which are reactive with the peptide and compete withthe target molecule, as well as enzyme-linked assays, which rely ondetecting an enzymatic activity associated with the target molecule.Each of these methods represents an additional embodiment of the presentinvention.

In another embodiment, the peptide is inhibited with an antibodydirected against it. Methods of producing antibodies are well known inthe art, and are described, for example, in Current Protocols inImmunology, Wiley and Sons, eds. Coligan et al. Each method represents aseparate embodiment of the present invention.

The term “antibody” refers, in one embodiment, to an antiserum. Inanother embodiment, “antibody” refers to a purified antibody. In anotherembodiment, “antibody” refers to a modification of a purified antibody.In another embodiment, the antibody is polyclonal. In anotherembodiment, the antibody is monoclonal. In another embodiment, theantibody is any other type of antibody known in the art, e.g, ahumanized, anti-idiotypic, chimeric, or single chain antibody; an Fab,F(ab′).sub.2, Fab expression library fragment, or an epitope-bindingfragment of an antibody. Each type of antibody represents a separateembodiment of the present invention.

In one embodiment, the peptide of methods and compositions of thepresent invention comprises one or more oxidized amino acids. In anotherembodiment, the peptide does not comprise an oxidized amino acid. Inanother embodiment, the amounts of one or more peptides with oxidizedamino acids are combined with non-oxidized peptides of the same sequencein a diagnostic method of the present invention. In another embodiment,the amounts of one or more peptides with oxidized amino acids areanalyzed together with non-oxidized peptides of the same sequence. Inanother embodiment, one or more peptides with oxidized amino acids areused as alternatives to non-oxidized peptides of the same sequence inmethods of the present invention. In another embodiment, an oxidationstate of a particular peptide of the present invention, or of aparticular amino acid of the peptide, is itself a labor marker. Eachpossibility represents a separate embodiment of the present invention

In another embodiment, the present invention provides a kit comprising areagent utilized in performing a method of the present invention. Inanother embodiment, the present invention provides a kit comprising acomposition, tool, or instrument of the present invention. In anotherembodiment, the present invention provides a kit used to perform amethod of the present invention. “Kit” refers, in another embodiment, apackage that facilitates a diagnostic or other procedure by providingmaterials or reagents needed thereof in a convenient format. In anotherembodiment, the kit comprises a means of detecting a peptide of thepresent invention. Each possibility represents a separate embodiment ofthe present invention.

EXPERIMENTAL DETAILS SECTION EXAMPLE 1 A Labor Diagnostic Test Utilizingthe Intensity of Amnion Protein Peaks Materials and Experimental Methods

Collection of Amnion Tissue Samples

Amnion tissue samples were collected from a region distal to theplacental insertion, from women either not in labor and undergoingelective cesarean section (CS; n=30); or following normal labor (n=30).All women were between 37 and 42 weeks (Naegele's Rule and/or obstetricultrasound), and had no vaginal bleeding and intact membranes Sampleswere washed with phosphate-buffered saline (PBS), and proteinhomogenates were prepared using a PBS-based lysis buffer containing 0.1%n-octyl-B-D-glucopyranoside, 1 mM sodium vanadate, 2 μg/ml leupeptin, 2μg/ml apiotinin, and 1 mM PMSF. Samples were centrifuged at 12,000 timesgravitational force (×g) (14,000 rpm) for 1 min (minute) and quantitatedby BCA protein assay kit (Pierce, Rockford, Ill.) prior to SELDIanalysis.

Surface-Enhanced Laser Desorption/Ionization (SELDI) Analysis

Before loading the samples, 50 μl binding buffer, pH 4 was applied toeach spot, and the chip was incubated at room temperature on a platformshaker for 5 minutes. This procedure was performed twice. Samples werediluted in pH 4 buffer (50 mM ammonium acetate, 0.1% Triton X-100, pH=4)to 25 ng/μl protein, and 50 μL of the diluted sample was applied to eachspot on a weak cation exchange (WCX2) Protein Chip (Ciphergen), using a96-well Bioprocessor (Ciphergen Bio-systems, Inc., Fremont, Calif.), adevice that holds 12 chips and allows application of larger volumes ofserum to each chip array. The Protein-Chip System is an affinity-basedmass spectrometric method in which proteins of interest are selectivelyadsorbed to a chemically modified surface on a biochip. After thesamples were incubated at room temperature for 60 minutes on a platformshaker, the array was washed three times with 50 μL of pH 4 buffer for 5minutes, followed by one rinse with 50 μL of the pH 4 diluted 1 to 100.After air-drying, 0.5 μL of saturated (20%) CHCA (α-cyano-4-hydroxycinnamic acid; the energy-absorbing molecules [EAM]) in 1:1acetonitrile: TFA was applied twice to each spot. Surface enhanced laserdesorption/ionization time of flight mass spectrometry (SELDI-TOF-MS)was then performed. The method is depicted in FIG. 1.

Spectra were obtained for each sample, normalized using the total ioncurrent, and peak differences and patterns were determined usingBiomarker Wizard software (BMW, Ciphergen Biosystems, Inc.) andClassification and Regression Tree software (CART), respectively.Specific peaks of interest were further identified using a MicromassQTOF II (Manchester, UK) tandem quadrupole-time of flight (Q-TOF) massspectrometer equipped with a PCI 1000 ProteinChip® Tandem MS Interface(Ciphergen Biosystems).

Statistical Analyses.

A p-value of less than 0.05 was used as the criteria for statisticalsignificance of peak intensity differences between groups.

Results

Amnion tissue samples were collected from women either not in labor andundergoing elective term cesarean section or following normal, termlabor, and were analyzed for protein peaks whose intensity differedbetween the two groups in a statistically significant manner. 17 suchpeaks were identified, 9 of which were stronger in the CS group, withthe other 8 stronger in the labor group. The M/Z (mass/charge ratios) ofthe peaks are listed in FIG. 2A. CART software was used to develop aclassification tree that segregated the samples as either CS or labor,utilizing the 3.214 kDa peak (SEQ ID No: 5), 4.023 kDa peak (SEQ ID No:12), and 3.712 kDa peak, and the 3.23 kDa peak (SEQ ID No: 6). Theclassification tree correctly identified 90% of the labor samples and96% of the CS samples.

EXAMPLE 2 Identification of Peptides Detected in Amnion Protein PeaksCorrelated with Labor Materials and Experimental Methods

Protein identification was performed by peptide fragmentation, using atandem mass spectrometer equipped with a PCI-1000 ProteinChip®(Ciphergen) Interface. Single MS and MS/MS spectra were acquired on atandem mass spectrometer, either a Q-Star® (ABI) or Q-TOF® (Micromass)equipped with a PCI-1000 ProteinChip Interface. Using ProteinChip Arraysas supplied, without further addition of CHCA, spectra were collected inthe 1-3 kDa range in single MS mode. After reviewing the spectra,specific ions were selected and introduced into the collision cell forCID fragmentation. The CID spectral data was submitted to thedatabase-mining tool Mascot (Matrix Sciences)®, a search engine thatuses mass spectrometry data to identify proteins from primary sequencedatabases.

Results

The 3.2 kDa peak cluster and several other peaks from Example 1 wereselected for identification. The 3.2 kDa peak cluster, the 3346 kDa peak(corresponding to the 3.343 kDa peak in FIG. 2A), and the 2.927 kDa peakwere determined to be fragments of the hemoglobin-α chain with orwithout oxidized amino acids, while the 2.541 kDa peak (corresponding tothe 2.529 kDa peak in FIG. 2A) was determined to be a fragment of serumalbumin (FIG. 3). The 2.927 kDa peak was identified by single MSanalysis, followed by a search for matches to the mass of humanhemoglobin alpha fragments.

The sequences of the identified peptides are depicted in Table 1:

TABLE 1 Sequences of identified amniotic peptides. SEQ Peak Protein/ ID(kDa) location Sequence No. 2.541 Serum DAHKSEVAHRFKDLGEENFKAL 1 albuminAA 24-45 2.927 Hemoglobin- VLSPADKTNVKAAWGKVGAHAGEYGAEAL 2 α AA 1-293.343 Hemoglobin- VLSPADKTNVKAAWGKVGAHAGEYGAEALERM 3 α AA 1-32 3.199Hemoglobin- VLSPADKTNVKAAWGKVGAHAGEYGAEALER 4 α AA 1-31 3.215Hemoglobin- (VLSPADKTNVKAAWGKVGAHAGEYGAEALER)* 5 α AA 3.231 Hemoglobin-VLSPADKTNVKAAW*GKVGAH*AGEYGAEALER 6 α AA 1-31 4.023 3.712 *oxidizedamino acid. The 3.215 kDa peptide contains one oxidized amino acid.

Thus, the findings of Examples 1 and 2 show that the amounts of variousproteins and peptides in the amnion are indicative of the labor statusof pregnant subjects.

EXAMPLE 3 A Labor Diagnostic Test Utilizing the Intensity ofCervicovaginal Secretion Protein Peaks Materials and ExperimentalMethods

Sample Collection

Vaginal secretion samples were collected from consenting patients at theHospital of the University of Pennsylvania, Philadelphia, Pa. All womenin the study were pregnant with a normal intra uterine single/twingestation. Patients within 37 and 42 weeks of pregnancy were classifiedas term. The gestational age was determined by Nagele's rule and/orobstetric ultrasound. Samples were only collected from patients withintact membranes and without vaginal bleeding. Cervicovaginal secretionsamples were collected using a cotton swab prior to the digitalexamination. The samples were collected in Dulbecco's phosphate bufferedsaline (DPBS, Invitrogen, Grand Island, N.Y.) containing a proteaseinhibitor cocktail (Complete Mini®, Roche, Indianapolis, Ind.) and theywere immediately flash frozen and stored at −80° C. until furtherevaluation. Labored and non-labored cervicovaginal secretions werespecifically segregated by close observation of uterine contraction andcervical evolution for at least one hour. Patients having none or fewcontractions, a closed or less than 3 cm dilation of the cervix, andbetween 0-50% cervical effacement were classified as not in labor(n=20). This diagnosis was contingent upon there being no changes incervical dilation or effacement after a second evaluation takenapproximately one hour later. Patients having active contractions,cervical effacement greater than 50% and dilation greater than 3 cm wereclassified as in labor if those parameters persisted and were determinedin the second evaluation (n=20).

Sample Preparation and Processing

All samples were extensively aliquotted to avoid repetitive freeze-thawcycles and stored at −80 C. Cervicovaginal fluid protein extracts werecleared via centrifugation at 14,000 rpm at 4 C and quantitated by theBCA protein assay kit (Pierce, Rockford, Ill.). All reagents, equipmentand software used during the proteomic analysis of the cervicovaginalsecretion samples, unless otherwise indicated, was purchased fromCiphergen Biosystem, Inc., Fremont Calif. Samples were then diluted inpH 4 buffer (50 mM ammonium acetate, 0.1% triton X-100, pH=4) andspotted (25 ng/μl protein) onto weak cation exchange chips (WCX-2).Chips were then dried and spotted twice with energy absorbing molecules(EAM, 20% CHCA) and subsequently analyzed using surface-enhanced laserdesorption/ionization, time of flight, mass spectrometry (SELDI-TOF—MS).Spectra were obtained for each sample, normalized using total ioncurrent, and peak differences and patterns were determined usingBiomarker Wizard® Software (BMW). Specific peaks were further identifiedat Ciphergen's Biomarker Discovery Center in Fremont, Calif. usingProtein Chip Interface Quadruple Time-of-Flight Mass Spectrometry(PCI-QTOF-MS).

Peptide Synthesis

After receiving peak identities, peptides were manufactured by GenemedSynthesis Inc., San Francisco, Calif. The 2.022 kDa peptide had thefollowing amino acid sequence and was amidated at the C terminus‘N-AAHLPAEFTPAVHASLDKF-C’. The control peptide was composed of the sameamino acids as the 2.022 kDa peptide, but the residues were orderedrandomly.

Statistical Analysis

During the proteomic analysis of the cervicovaginal fluids, T-tests wereperformed to determine statistical differences (P<0.05) between the peakintensity of the labored and the unlabored groups. In the cellularcontraction studies, results were expressed as the mean±standard erroras indicated. Differences between the potentiation and control peptidegroups were assessed using a 2-way ANOVA. Additionally,concentration-dependent differences between the values of thepotentiating and control peptide were assessed via 1-way ANOVA with apost-test for linear trend. P-values <0.05 were classified asstatistically significant.

Results

Cervicovaginal fluid samples were collected from pregnant subjects atfull term either in labor (n=20) or not in labor (n=20). 25 proteinpeaks whose intensity differed between the two groups in a statisticallysignificant manner were identified. 12 of the peaks exhibited greaterintensity in non-laboring subjects, while 13 peaks exhibited greaterintensity in laboring subjects (FIG. 4A). CART software was used todevelop a classification tree that segregated the samples as either CSor labor, utilizing the 1.869 kDa peptide (SEQ ID No: 10), the 3.908 kDapeptide, and the 3.196 kDa peptide (SEQ ID No: 7). The classificationtree correctly identified 100% of the labor samples and 95% of thenon-labor samples. Several peaks or clusters of peaks, including the 3.2kDa cluster and the 1.869 kDa, 3.908 kDa, 2.022 kDa, 3.275 kDa, and3.279 kDa peptides, were particularly useful in classifying the samples.

EXAMPLE 4 Identification of Peptides Detected in CervicovaginalSecretion Protein Peaks Correlated with Labor

Several peaks from Example 3 were selected for identification. Thecomponents of all of the identified peaks were found to be fragments ofhemoglobin. The 3.277 kDa peak was found to contain 2 peptides of 3.275and 3.279 kDa. Specifically, the components of the 3.196 kDa(corresponding to the 3.198 kDa peak of FIG. 4A), 3.228 kDa, 2.022 kDa,and 3.279 (corresponding to the 3.277 kDa peak of FIG. 4A) peaks werefragments of the α-chain, and the components of the 1.869 and 3.275 kDapeaks were fragments of the β-chain of hemoglobin (FIG. 5). The 3.228kDa peak contained the same peptide as the 3.231 kDa amniotic peptidedescribed above.

The identified peptides are depicted in Table 2. Spectra from eachsample were collected, data was normalized by the total ion current, andanalyzed using Biomarker Wizard software. Depicted are molecular weightand respective p-values of the peaks that were found to be statisticallydifferent (P<0.05) between cervicovaginal fluid collected at term frompatients experiencing labor and patients who are not in labor.

TABLE 2 Sequences of identified cervicovaginal peptides. SEQ PeakProtein/ ID (kDa) location Sequence No. 3.196 Hemoglobin-VLSPADKTNVKAAWGKVGAHAGEYGAEALER 7 α AA 1-31 3.228 Hemoglobin-VLSPADKTNVKAAW*GKVGAH*AGEYGAEALER 8 α AA 1-31 2.022 Hemoglobin-AAHLPAEFTPAVHASLDKF 9 α AA 110-128 1.869 Hemoglobin- YQKVVAGVANALAHKYH10 β AA 130-146 3.279 Hemoglobin- ADKTNVKAAWGKVGAHAGEYGAEALERMFLS 11 αAA 5-35 3.275 Hemoglobin- VHLTPEEKSAVTALWGKVNVDEVGGEALGRL 12 β AA 1-313.908 1.799 2.846 3.153 3.250 3.309 3.329 3.783 3.852 3.908 4.738 4.8935.072 5.434 6.184 6.606 7.051 7.240 7.343 9.807 *oxidized amino acid.

Thus, the findings of Examples 3-4 show that the amounts of variousproteins and peptides in cervicovaginal fluid are markers for the laborstatus of a subject.

EXAMPLE 5 Inverse Correlations Between Amnion and CervicovaginalSecretion Protein Peaks

A comparison of the amnion and cervicovaginal secretion protein peakpatterns is shown in FIG. 6. A number of the peaks exhibited increasedintensity in amniotic tissue samples collected from non-laboring CSsubjects than laboring subjects and increased intensity incervicovaginal samples collected from laboring subjects thannon-laboring subjects. The intensity of the 3.2 kDa cluster ofα-hemoglobin peptides, for example, was found to be a statisticallysignificant correlate of labor in both the amnion and cervicovaginalsecretions.

These findings show that some biomarkers of labor, for the example the3.2 kDa cluster of α-hemoglobin peptides and other peptides listedabove, are stored in the amnion and released with the onset of laborinto other biological fluids, including, for example, cervicovaginalsecretions, urine, serum, blood plasma, and saliva. The presence ofthese peptides in various biological fluids can thus be used indiagnosing term and/or preterm labor.

EXAMPLE 6 Refinement of Labor Diagnostic Methods Using the Chemstriptest, and its use in Diagnosing Labor in Both Term and Preterm SubjectsMaterials and Experimental Methods

Inclusion Criteria

Pregnant subjects between 22 and 36 weeks, 6 days gestational agesuspected of being in preterm labor were recruited, with inclusioncriteria otherwise the same as described in Example 1.

Statistical Analyses

Data from the term- and preterm subjects were combined and analyzed in asingle group. The Chemstrip® test was performed and evaluated in ablinded manner. The results “negative,” “trace,” “++,” and “+++” wereassigned values of 0, 1, 2, and 3, respectively. The proportion ofsubjects in labor for each of the levels of the Chemstrip® test werecomputed, and the test of linear trend was conducted for the Chemstrip®test using the Cochran-Armitage trend test. In addition, mean intensityvalues of the 1.869 kDa and 3.198 kDa peaks were computed for eachgroup. The data are depicted in the tables below:

Chemstrip ® test: Chemstrip ® score. 0 1 2 3 Total Not in labor 3 6 9 220 % of non-labor samples 15.00 45.00 30.00 10.00 with this score % ofsamples with this score not in 75.00 81.82 54.55 13.33 labor In labor 12 5 13 21 % of labor samples with this score 4.76 9.52 23.81 61.90 % ofsamples with this score 25.00 18.18 45.45 86.67 in labor

-   -   Cochran-Armitage trend test results:        -   Statistic (Z) −3.4267        -   One-sided Pr<Z 0.0003        -   Two-sided Pr>|Z|0.0006

3.198 kDa and 1.869 kDa peaks Variable N Mean Std dev Minimum MaximumNON-LABOR SUBJECTS Peak Intensity 3.198 kDa 20 0.524 0.676 −0.39982.6541 (inten1) Peak Intensity 1.869 kDa 20 0.207 0.439 −0.8789 1.5772(inten2) LABOR SUBJECTS Peak Intensity 3.198 kDa 21 7.020 9.955 −0.297341.2945 (inten1) Peak Intensity 1.869 kDa 21 2.366 2.712 −0.1922 8.8463(inten2)

Receiver operating characteristic (ROC) curves were used to ascertainthe ability to diagnose labor of the Chemstrip® data and the intensitymeasures of the 1.869 kDa and 3.198 kDa peaks (referred to as “inten1”and “inten2”, respectively). For each level of the marker, thesensitivity as well as specificity were estimated and plotted (FIG. 7A).The area under the ROC curve is reflective of the ability of each markerto assign subjects to the correct category (labor vs non-labor).Comparisons among ROC curves defined for the same set of women wereconducted using a non-parametric method described by (DeLong E R et al,Biometrics 44(3): 837-45, 1988). While all three markers exhibitedstrong diagnostic power, the diagnostic power of the 1.869 kDa peakintensity was the highest. The results are depicted below:

ROC Asymptotic Normal Obs Area Std. Err. [95% Conf. Interval] Hemoglobin41 0.8060 0.0683 0.67207 0.93983 Inten1 41 0.8286 0.0682 0.69483 0.96231Inten2 41 0.8476 0.0666 0.71714 0.97809 Ho: area(hemo) =area(intensity1) = area(intensity2) chi2(2) = 0.28 Prob > chi2 = 0.8696

Next, Pearson correlation coefficients were used to ascertain the extentof correlation between the three measures. The results are depicted inthe chart below. The Chemstrip measure exhibited a moderate correlationwith the other two markers, (r_(—)1=0.372 and r_(—)2=0.447), while thetwo peak markers were more highly correlated (r=0.865).

Prob > |r| under H0: Rho = 0 hemo inten1/p-value inten2/p-value hemo 10.37186 0.44678 0.0167 0.0034 inten1 0.37186 1 0.86491 0.0167 <.0001inten2 0.44678 0.86491 1 0.0034 <.0001

Next, combinations of the markers were considered using logisticregression models. All possible combinations of markers were considered,and the best model was selected, using model selection techniques basedon the following characteristics: 1) markers included in the model wereindependent predictors of labor status, as defined by p-value <0.05; 2)there was minimal collinearity of the model parameters, as defined bythe correlation among the coefficient estimates; and 3) a statisticallysignificant increase in the area under the ROC curve was observed, asdescribed in DeLong, ibid. The statistics package STATA® was used forall statistical models described.

Univariate analysis was first used to ascertain the predictive power ofeach variable separately. Hemoglobin was the strongest independentpredictor of probability of labor, as depicted below:

A. model: ln[pr(labor)/{1−pr(labor}=intercept+estimate*(hemo).

In this model and all those that follow (B-F), the values for“intercept,” 10 “estimate,” “estimate1,” etc, used in the equation arethose found in the “estimate” column of the table labeled “Analysis ofMaximum Likelihood Estimates.” Thus, in this case the formula used wasln[pr(labor)/{1−pr(labor}=−1.324+2.5004*(hemo).

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 13.0202 1 0.0003 Score 11.7423 1 0.0006 Wald 9.4148 10.0022

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq hemo 1 2.5004 0.9249 7.3091 0.0069 Intercept1 −1.3240 0.4315 9.4148 0.0022

B. model: ln[pr(labor)/{1−pr(labor}=intercept+estimate*(inten1)

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 18.8429 1 <.0001 Score 7.3147 1 0.0068 Wald 4.2431 10.0394

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq Intercept 1 −1.2249 0.5183 5.5855 0.0181inten1 1 0.8634 0.4192 4.2431 0.0394

C. model: ln[pr(labor)/{1−pr(labor}=intercept+estimate*(inten2)

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 17.2493 1 <.0001 Score 9.8654 1 0.0017 Wald 4.2035 10.0403

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq Intercept 1 −1.0954 0.4974 4.8486 0.0277inten1 1 1.8086 0.8821 4.2035 0.0403

Since hemoglobin was the strongest independent predictor of probabilityof labor, hemoglobin was combined with each of the peak valuesseparately in the following models. The regression coefficient estimatesfor intens1 and 2 showed significant correlation. Hemoglobin was still asignificant predictor even in the presence of the other 2 measures. Theresults are depicted below:

D. Fit.model:ln[pr(labor)/{1−pr(labor}=intercept+estimate1*(hemo)+estimate2*(inten1)

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 24.4413 2 <.0001 Score 14.1164 2 0.0009 Wald 7.9837 20.0185

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq Intercept 1 −3.2451 1.1907 7.4284 0.0064hemo 1 1.1840 0.5491 4.6497 0.0311 inten1 1 0.6786 0.3625 3.5042 0.0612Odds Ratio Estimates 95% Wald Effect Point Estimate Confidence Limitshemo 0.306 0.104 0.898 inten1 0.507 0.249 1.032

E. Fit model:ln[pr(labor){1−pr(labor}=intercept+estimate1*(hemo)+estimate2*(inten2)

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 22.2498 2 <.0001 Score 14.9806 2 0.0006 Wald 7.5904 20.0225

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq Intercept 1 −2.8111 1.0609 7.0206 0.0081hemo 1 1.0134 0.4844 4.3771 0.0364 inten2 1 1.5081 0.7537 4.0031 0.0454

F. Fit model:ln[pr(labor)/{1−pr(labor}=intercept+estimate1*(hemo)+estimate2*(inten1)+estimate3*(inten2)

Testing Global Null Hypothesis: BETA = 0 Test Chi-Square DF Pr > ChiSqLikelihood Ratio 24.5784 3 <.0001 Score 14.9830 3 0.0018 Wald 7.6166 30.0546

Analysis of Maximum Likelihood Estimates Standard Parameter DF EstimateError Chi-Square Pr > ChiSq Intercept 1 −3.1780 1.1902 7.1301 0.0076hemo 1 1.1236 0.5658 3.9437 0.0470 inten1 1 0.5839 0.4502 1.6820 0.1947inten2 1 0.3500 0.9912 0.1247 0.7240 Estimated Correlation MatrixVariable Intercept hemo inten1 inten2 Intercept 1 −0.8764 −0.3068 0.1038hemo −0.8764 1 0.1424 −0.2623 inten1 −0.3068 0.1424 1 −0.5074 inten20.1038 −0.2623 −0.5074 1

ROC curves and predicted probabilities were also used to evaluate thepredictive power of several variables in isolation and combinations. TheROC curves are depicted in FIG. 7B-E. The resulting pseudo R² values ofall combinations, a measure of the amount of variability in the response(i.e. probability of labor) that is accounted for by the model, aredepicted in the table below:

Pseudo-R2 from STATA Model Pseudo R² logistic labor hemo Pseudo R² =0.2292 logistic labor inten1 Pseudo R² = 0.3317 logistic labor inten2Pseudo R² = 0.3036 logistic labor hemo inten1 Pseudo R² = 0.4302logistic labor hemo inten2 Pseudo R² = 0.3916 logistic labor inten1inten2 Pseudo R² = 0.3522 logistic labor hemo inten1 inten2 Pseudo R² =0.4326

Thus, the results of the non-parametric method and the logisticregression models confirmed one another and showed that the hemoglobinvalue and the intensity of the 1.869 kDa peak were the combination oftwo variables with the greatest predictive power. Including theintensity of the 3.198 kDa peak slightly increased the pseudo R² value.

Results

The hemoglobin levels of samples from the subjects of the previousExamples, and from the subjects recruited in the present Example, weretested using the Chemstrip 6® (Roche) urine multi-parameter test strip.A correlation between the total amount of hemoglobin in the samples andthe labor status of the subjects was observed. Logistic regressionmodels were then used to determine the best diagnostic combination,among the Chemstrip test and the SELDI peak intensity values of the1.869 kDa and 3.198 kDa peaks. The best diagnostic test was found to bethe combination of the Chemstrip results and the intensity of the 1.869kDa peak, which increased sensitivity from 61.9% to 90.5% and improvedspecificity from 84.7% to 89.7%, relative to the 1.869 kDa peak alone,as shown by ROC (receiver operating characteristic) curves (FIG. 7A-B).Using this test, 90.5% of the subjects in labor and 89.7% of thesubjects not in labor were correctly identified. The raw data from theanalyses is depicted in FIG. 8. The following model was found to havethe optimum predictive power:ln[pr(labor)/{1−pr(labor} 2.81−1.01(x)−1.51(y),wherein p=the probability of being in labor

-   -   x=the Chemstrip score, as defined above; and    -   y=the intensity of the 1.869 kDa peak.

Thus, accurate diagnostic methods for detecting and predicting labor inboth term and preterm pregnant subjects can be designed, using thepeptides of the present invention.

EXAMPLE 7 Two of the Labor Markers Exhibit Structures of BiologicallyActive Peptides Materials and Experimental Methods

Peptide Synthesis

Peptide synthesis was performed by Genemed Synthesis.

Results

Two of the fragments identified in the above analysis were synthesized;namely, amino acids 110-128 of α-chain hemoglobin (SEQ ID No: 9), andamino acids 130-146 of β-chain hemoglobin (SEQ ID No: 10). The firstfragment exhibited a structure of a peptide with bradykinin potentiatingactivity.

These findings show that a peptide containing amino acids 110-128 ofα-chain hemoglobin increases vascular permeability.

EXAMPLE 8 Identification of Additional Labor Markers from PreviousExamples

The protocol described in Example 2 is used to identify the other labormarkers depicted in FIGS. 2A and 4A. Identification of these markersenables the use of additional tests such as any of various knownimmuno-assays, to assess their concentrations, thus modifying thediagnostic tests of the present invention.

EXAMPLE 9 Isolation and Identification of Additional Labor Markers

SELDI, mass spectrometry, and CART analysis are used to isolate andidentify additional labor markers as described in Examples 1-4. Theadditional markers are used to further enhance the sensitivity andspecificity of the diagnostic algorithms of the present invention.

EXAMPLE 10 Multivariate Statistical Analysis of Labor Markers

CART analysis is used to analyze the marker proteins identified inExamples 1-5 in combination with maternal age, gestational age,reproductive history, serum hCG level, and/or other known factors, toimprove their accuracy in predicting and/or detecting the onset oflabor.

EXAMPLE 11 Use of Multivariate Statistical Analysis to IdentifyAdditional Labor Markers

CART analysis is performed on candidate marker protein concentrations incombination with maternal age, gestational age, reproductive history,serum hCG level, and/or other known factors. This analysis will identifymarker proteins that are diagnostic of labor when considered incombination with the additional factor(s), even though the concentrationof the marker protein, when considered alone, may have less or nodiagnostic value.

EXAMPLE 12 The 2.022 kDa Peptide Exhibits Uterotonic PotentiatingActivity Materials and Experimental Methods

Gels for Smooth Muscle Cells Activation Bioassay

PA gels of controlled stiffness were coated with a nearly constantcollagen level (5×10² ng/cm²) as assessed by fluorescent collagenintensities. Nanometer-scale gel stiffness was measured by AFM, usingcantilever tips with radii of curvature <50 nm.

Bioassay of Smooth Muscle Activating Peptides

To assess the ability of peptides found in cervicovaginal fluid toactivate smooth muscle cells, rat aorta-derived A7R5 vascular smoothmuscle cells (A7R5; ATCC, Manassas, Va.) were plated onto polyacrylamidegel surfaces (34 kPa) with collagen type 1 (BD Biosciences, San Diego)and covalently pre-attached to the gel surface by sulpho-SANPAH (Pierce,Rockland, Ill.), providing a quantitative and reproducible uterotonicsactivity assay. Cells were permitted to adhere to the surface for 30minutes, then were incubated at 37° C. for 4 hours with bradykinin (0-1μM, Sigma-Aldrich, St. Louis, Mo.), oxytocin (0-1 μM, Sigma-Aldrich) orthe prostanoid PGF2α (0-0.1 μM, Sigma-Aldrich) +/− varying doses of the2.022 kDa peptide or the control peptide, in which the sequence wasscrambled, after which they were observed on a Nikon TE300 invertedmicroscope with an attached cooled CCD camera. Cellular areameasurements were made using Image1 software 1.321 (NIH) from a largenumber of cells (n>50/culture). Data was fit to a hyperbolic expressionusing a least squared method, with the half-saturation constant (IC₅₀)representing the intermediate set-point for the system.

In other assays, human uterine smooth muscle cells (UtSMC) were treatedwith 10 nM bradykinin, 0.5 μM prostaglandin 2α (PGF2α), or 50 nMoxytocin, in the absence or presence of 5 μg/ml of the 2.022 kDapeptide, or with 10 μg/ml peptide alone. Numbers of contracted cells(exhibiting a shorter, rounded morphology) were quantitated.

Oxytocin Potentiation Assay

The oxytocin potentiation tissue assay was performed by MDS PharmaService, Taipei, Taiwan. Briefly, pregnant Wistar rat uteri (325±25 g)were isolated and suspended in an isometric tissue bath containing Krebsbuffer, pH 7.4. The uteri were treated with 1 nM oxytocin +/− the 2.022kDa peptide (100 μM), the control peptide (100 μM), distilled water, orphosphoramidon (30 μM), which inhibits oxytocin breakdown as a positivecontrol, and incubated for 5 minutes at 32 C. Tissue reactivity (n=2)was quantitatively assessed after five minutes by recording isometriccontractions (gm changes).

Results

To determine whether the 2.022 kDa fragment, amino acids 110-128 ofα-chain hemoglobin (SEQ ID No: 9), acts as a bradykinin potentiationfactor, agonist-induced cell shape change studies were performed onbradykinin-treated and untreated vascular smooth muscle cells. Tomeasure cell contractility, A7R5 cells were plated on collagen-coatedhydrogels and were permitted to adhere and spread to a certain cellarea, which is dependent upon myosin contractility. Bradykinin treatmentresulted in a hyper-contractile cell morphology, which significantlylimited cell spreading with an IC₅₀ of 5 nM. When the 2.022 kDa peptide(PP) or a control peptide (CP) was added together with a half-saturationdose of bradykinin (5 nM), the 2.022 kDa peptide augmented thebradykinin response, and cell area was decreased maximally (P 0.0004;half-saturation effect of the peptide: 9.346 μM) (FIG. 10A). Bycontrast, the decrease in cell area elicited by maximal doses ofbradykinin (1 μM) was not affected by the 2.022 kDa peptide. Neither the2.022 kDa peptide nor the control peptide had an effect on cell areawhen administered without bradykinin. As expected, the control peptidedid not affect the bradykinin response (P=0.95).

To determine whether the 2.022 kDa peptide enhances the effects of otheragents that promote smooth muscle contraction, the effect of the peptideon oxytocin- and PGF2α-induced contraction was determined. Oxytocin andPGF2≢0 decreased cell area with IC 50s of 8 nM and 1 nM, respectively(FIG. 10B-C). This decrease in cell area was enhanced by sub-μM amountsof the 2.022 kDa peptide, with maximal enhancement occurring atapproximately half the saturation dose of oxytocin or PGF2α (FIG. 2 Band C, see Δ effect, P=0.0011 and P<0.0001, respectively).

In addition, the ability of the 2.022 kDa peptide to augment the effectsof oxytocin on uterine tissue was evaluated utilizing an isometrictissue bath. Administration of 30 μM phosphoramidon, a proteaseinhibitor, served as the positive control. The 2.022 kDa peptide (100μM) increased uterine contraction in the presence of oxytocin by 30%compared to the negative controls (distilled water or 100 μM of thecontrol peptide), as depicted in FIG. 11.

These results show that the 2.022 kDa peptide exhibits uterotonicpotentiating activity, demonstrating that this peptide plays a role inlabor induction. Thus, an antagonist of this peptide is useful inpreventing labor.

EXAMPLE 13 Identification of Inhibitors of the 2.022 kDa Peptide

Inhibitors of the 2.022 kDa peptide are produced by designing andproducing small molecule inhibitors, using one of the methods describedin, for example, Tanuma S et al (Biol Pharm Bull 27(7): 968-73, 2004;Raimundo B et al (J Med Chem 47(12): 3111-30, 2004; Wang J et al, ProcNatl Acad Sci USA 97(13): 7124-9; 2000; and Huang J et al, (Proc. Natl.Acad. Sci. USA 94: 13396-13401, 1997). Alternatively, antibodies areraised to the 2.022 kDa peptide. Alternatively, a biological target ofthe 2.022 kDa peptide is identified, and molecules that inhibitinteraction between the peptide and its target are identified, using oneof the above methods.

EXAMPLE 14 Testing Inhibitors of the 2.022 kDa Peptide in an AnimalModel for Inhibition of Induction of Labor

The inhibitors of the 2.022 kDa peptide identified in the previousExample are tested in an animal model for inhibition of induction oflabor, such as that described in Gross G et al, Am J Physiol RegulIntegr Comp Physio 278(6): R1415-23, 2000; Dieni S et al, J NeuropatholExp Neuro 63(12): 1297-309, 2004; or Chellman G et al, Reprod Toxicol18(2): 285-93, 2004. Inhibition of induction of labor in the animalmodel indicates that the peptide and variants and homologues thereof areuseful in inhibiting labor in human and animal subjects.38

1. A method of predicting or detecting labor in a female subject,comprising a. determining an amount of a first peptide in a biologicalsample of said female subject, said first peptide having the amino acidsequence set forth in SEQ ID No: 10; b. comparing said amount of saidfirst peptide to a reference standard for said first peptide; c.determining an amount of a second peptide, said second peptide havingthe amino acid sequence set forth in SEQ ID No: 7, wherein said amountis an amount in said biological sample or an additional biologicalsample of said female subject; and d. comparing said amount of saidsecond peptide to a reference standard for said second peptide, wherebyif: (i) both (i a) said amount of said first peptide is higher than anupper limit of a range defined by said reference standard for said firstpeptide; and (i b) said amount of said second peptide is higher than anupper limit of a range defined by said reference standard for saidsecond peptide, then said female subject is in labor; and if: (ii) both(ii a) said amount of said first peptide is higher than said upper limitof said range defined by said reference standard for said first peptide;and (ii b) said amount of said second peptide is lower than a lowerlimit of said range defined by said reference standard for said secondpeptide, then said female subject is not in labor.
 2. The method ofclaim 1, wherein said first peptide comprises an oxidized amino acid. 3.The method of claim 1, wherein said second peptide comprises an oxidizedamino acid.
 4. The method of claim 1, whereby at least one of (a) thestep of determining said amount of said first peptide; and (b) the stepof determining said amount of said second peptide comprises animmunological assay.
 5. The method of claim 1, wherein at least one of(a) said biological sample and (b) said additional biological sample isa cervicovaginal secretion.
 6. The method of claim 1, wherein said laboris a preterm labor.